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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Enhanced Habitability on High Obliquity Bodies Near the Outer Edge of the Habitable Zone of Sun-Like Stars

High obliquity planets represent potentially extreme limits of terrestrial climate, as they exhibit large seasonality, a reversed annual-mean pole-to-equator gradient of stellar heating, and novel cryospheres. A suite of 3-D global climate model simulations with a dynamic ocean is performed with Earthlike atmospheres for low and high obliquity planets with various stellar fluxes, CO2 concentrations, and initial conditions to explore the propensity for high obliquity climates approaching the outer edge of the Habitable Zone to undergo global glaciation. We also simulate planets with thick CO2 or H2 atmospheres, such as those expected to develop near or beyond the outer edge of the Habitable Zone. We show that high obliquity planets are hotter than their low obliquity counterparts due to ice-albedo feedbacks for cold climates, and water vapor in warm climates. We suggest that the water vapor greenhouse trapping is greater on high obliquity bodies due to the different dynamical regimes that occur between the two states. While equatorial ice-belts are stable at high obliquity in some climate regimes, it is harder to achieve global glaciation than for a low obliquity planet. Temperate polar conditions can be present at high obliquity at forcings for which low obliquity planets would be in a hard snowball state. We suggest the conditions on high obliquity planets are likely to be more favorable for a robust biosphere to develop approaching the outer edge of the HZ. However, the influence of obliquity diminishes for dense atmospheres, in agreement with calculations from 1-D Energy Balance Models.

planets and satellites: atmospheres↗
NASA NTRS1984

The influence of ocean surface temperature gradient and continentality on the Walker circulation. I - Prescribed tropical changes

A coarse mesh global climate model has been developed to assess ocean surface temperature (OST) gradient and continentality influences on the Walker circulation, which is characterized in the zonal plane by three pairs of clockwise and counterclockwise cells in the troposphere. The model response exhibits statistically significant changes in the intensity of the various cells and branches with small shifts in the east-west extent. The overall structure in the zonal plane for experiments with the coldest and with mean temperatures, however, remained unchanged. In an experiment involving the replacement of the South American continent by an ocean with OSTs linearly interpolated from the eastern Pacific to the western Atlantic, a dramatic change took place in the structure of the Walker circulation. It is concluded that both continentality and OST gradient are important Walker circulation forcing mechanisms.

Chervin, R. M.↗
NASA NTRS2011

Estimation and Validation of Oceanic Mass Circulation from the GRACE Mission

Since the launch of the Gravity Recovery And Climate Experiment (GRACE) in March 2002, the Earth's surface mass variations have been monitored with unprecedented accuracy and resolution. Compared to the classical spherical harmonic solutions, global high-resolution mascon solutions allows the retrieval of mass variations with higher spatial and temporal sampling (2 degrees and 10 days). We present here the validation of the GRACE global mascon solutions by comparing mass estimates to a set of about 100 ocean bottom pressure (OSP) records, and show that the forward modelling of continental hydrology prior to the inversion of the K-band range rate data allows better estimates of ocean mass variations. We also validate our GRACE results to OSP variations modelled by different state-of-the-art ocean general circulation models, including ECCO (Estimating the Circulation and Climate of the Ocean) and operational and reanalysis from the MERCATOR project.

Boy, J.-P.↗
NASA NTRS2019

The Role of Oceanic Processes in the Initiation of Boreal Winter Intraseasonal Oscillations over the Indian Ocean

Observational analyses and a hierarchy of ocean general circulation model (OGCM) experiments were performed to understand the influence of oceanic processes on the warm sea surface temperature anomalies (SSTAs) prior to the convection initiation of boreal winter intraseasonal oscillations (ISOs), including the Madden-Julian Oscillation (MJO), in the equatorial Indian Ocean. We found 39 strong ISOs that passed over the Indian Ocean Warm Pool region during the November-April season of the 2001-2012 period. 17/39 ISO events initiated in the Seychelles-Chagos Thermocline Ridge (SCTR) before propagating eastward; the remaining events initiated in the southern Arabian Sea (6) or Warm Pool (16) regions. The SCTR event set was notable in that it contained more global-scale MJOs (71-76%), as defined by the RMM and OMI indices, than the WP events (25-44%). Additionally, ~24% (44%) of the SCTR (Warm Pool) events were preceded by strong oceanic process-induced SSTAs of similar magnitude to those of shortwave radiative and turbulent heat fluxes. The Arabian Sea events, however, were not associated with statistically significant SSTA signals prior to convection. Based on a mixed layer heat budget analysis, entrainment and upwelling reduction were the dominant oceanic processes contributing to the warming, in contrast with boreal summer, when horizontal advection dominated. We examined several case studies, including primary MJO events, where oceanic Rossby waves were associated with the entrainment and upwelling reduction. Two simple atmospheric boundary layer convergence models revealed that the SSTAs contributed at least half of the total convergence and suggested that the ocean dynamical effect was responsible for the majority of SSTA-forced convergence for those case studies. These results underscore the need for climate prediction models to accurately represent the ocean structure and processes to include the effects of oceanic predictors.

West, B. Jason↗
NASA NTRS2012

The Added Value to Global Model Projections of Climate Change by Dynamical Downscaling: A Case Study over the Continental U.S. using the GISS-ModelE2 and WRF Models

Dynamical downscaling is being increasingly used for climate change studies, wherein the climates simulated by a coupled atmosphere-ocean general circulation model (AOGCM) for a historical and a future (projected) decade are used to drive a regional climate model (RCM) over a specific area. While previous studies have demonstrated that RCMs can add value to AOGCM-simulated climatologies over different world regions, it is unclear as to whether or not this translates to a better reproduction of the observed climate change therein. We address this issue over the continental U.S. using the GISS-ModelE2 and WRF models, a state-of-the-science AOGCM and RCM, respectively. As configured here, the RCM does not effect holistic improvement in the seasonally and regionally averaged surface air temperature or precipitation for the individual historical decades. Insofar as the climate change between the two decades is concerned, the RCM does improve upon the AOGCM when nudged in the domain proper, but only modestly so. Further, the analysis indicates that there is not a strong relationship between skill in capturing climatological means and skill in capturing climate change. Though additional research would be needed to demonstrate the robustness of this finding in AOGCM/RCM models generally, the evidence indicates that, for climate change studies, the most important factor is the skill of the driving global model itself, suggesting that highest priority should be given to improving the long-range climate skill of AOGCMs.

Racherla, P. N.↗
NASA NTRS2018

SMAP Mission Status, New Products, and Extended-Phase Goals

NASA's Soil Moisture Active Passive (SMAP) Project now has completed its prime-phase (three years) mission and has entered a new five-year extended phase. The global L-band radiometry from SMAP has enabled diverse scientific investigations in water, energy and carbon cycle research, terrestrial ecology and ocean science. These include eliciting the role of soil moisture control on the evaporation regime and vegetation gross primary productivity, observing soil-vegetation continuum water relations, analysis of flood and droughts, climate modeling and weather prediction, detecting ocean high-winds during tropical storms, and observing fresh-water outflow in coastal oceans. This paper highlights the recent enhancements to the SMAP suite of science products (from instrument level-1 to geophysical retrievals level-2 and level-3).

NASA Soil Moisture Active Passive (SMAP)↗
NASA NTRS2021

Non-Monotonic Response of the Climate System to Abrupt CO2 Forcing

We explore the climate system response to abrupt CO2 forcing, spanning the range 1 × to 8×CO2, with two state-of-the-art coupled atmosphere-ocean-sea-ice-land models: the NASA Goddard Institute for Space Studies Model E2.1-G (GISS-E2.1-G) and the Community Earth System Model (CESM-LE). We find that the effective climate sensitivity is a non-monotonic function of CO2 in both models, reaching a minimum at 3×CO2 for GISS-E2.1-G, and 4×CO2 for CESM-LE. A similar non-monotonic response is found in Northern Hemisphere surface temperature, sea-ice, precipitation, the latitude of zero precipitation minus-evaporation, and the strength of the Hadley cell. Interestingly, the Atlantic meridional overturning circulation collapses when non-monotonicity appears and does not recover for larger CO2 forcings. Analyzing the climate response over the same CO2 range with slab ocean versions of the same models, we demonstrate that the climate system's non-monotonic response is linked to ocean dynamics.

Non-monotonic response↗
NASA NTRS2015

AgMIP Climate Data and Scenarios for Integrated Assessment

Climate change presents a great challenge to the agricultural sector as changes in precipitation, temperature, humidity, and circulation patterns alter the climatic conditions upon which many agricultural systems rely. Projections of future climate conditions are inherently uncertain owing to a lack of clarity on how society will develop, policies that may be implemented to reduce greenhouse-gas (GHG) emissions, and complexities in modeling the atmosphere, ocean, land, cryosphere, and biosphere components of the climate system. Global climate models (GCMs) are based on well-established physics of each climate component that enable the models to project climate responses to changing GHG concentration scenarios (Stocker et al., 2013).The most recent iteration of the Coupled Model Intercomparison Project (CMIP5; Taylor et al., 2012) utilized representative concentration pathways (RCPs) to cover the range of plausible GHG concentrations out past the year 2100, with RCP8.5 representing an extreme scenario and RCP4.5 representing a lower concentrations scenario (Moss et al., 2010).

agriculture↗
NASA NTRS2022

The Impact of Winds on AMOC in a Fully-Coupled Climate Model

Here we investigate the role of the atmospheric circulation in AMOC by comparing a fully-coupled large ensemble, a forced-ocean simulation, and new experiments using a fully-coupled global climate model where winds above the boundary layer are nudged towards reanalysis. When winds are nudged north of 45°N, agreement with RAPID array observations of AMOC at 26.5°N improves across several metrics. The phasing of interannual variability is well-captured due to the response of the local Ekman component in both wind-nudging and forced-ocean simulations, however the variance remains underestimated. The mean AMOC strength is substantially reduced relative to the fully-coupled model large ensemble, which is biased high, due to the impact of winds on surface buoyancy fluxes over the subpolar gyre. Nudging winds towards observations also reduces the 1979-2016 trend in AMOC, suggesting that improvement in the representation of the high-latitude atmosphere is important for projecting long-term AMOC changes.

AMOC↗
NASA NTRS2014

CMIP5 Historical Simulations (1850-2012) with GISS ModelE2

Observations of climate change during the CMIP5 extended historical period (1850-2012) are compared to trends simulated by six versions of the NASA Goddard Institute for Space Studies ModelE2 Earth System Model. The six models are constructed from three versions of the ModelE2 atmospheric general circulation model, distinguished by their treatment of atmospheric composition and the aerosol indirect effect, combined with two ocean general circulation models, HYCOM and Russell. Forcings that perturb the model climate during the historical period are described. Five-member ensemble averages from each of the six versions of ModelE2 simulate trends of surface air temperature, atmospheric temperature, sea ice and ocean heat content that are in general agreement with observed trends, although simulated warming is slightly excessive within the past decade. Only simulations that include increasing concentrations of long-lived greenhouse gases match the warming observed during the twentieth century. Differences in twentieth-century warming among the six model versions can be attributed to differences in climate sensitivity, aerosol and ozone forcing, and heat uptake by the deep ocean. Coupled models with HYCOM export less heat to the deep ocean, associated with reduced surface warming in regions of deepwater formation, but greater warming elsewhere at high latitudes along with reduced sea ice. All ensembles show twentieth-century annular trends toward reduced surface pressure at southern high latitudes and a poleward shift of the midlatitude westerlies, consistent with observations.

ocean heat content↗
NASA NTRS2002

Comparison of Mean Climate Trends in the Northern Hemisphere Between N.C.E.P. and Two Atmosphere-Ocean Model Forced Runs

Results are presented for two greenhouse gas experiments of the Goddard Institute for Space Studies Atmosphere-Ocean Model (AOM). The computed trends of surface pressure, surface temperature, 850, 500 and 200 mb geopotential heights and related temperatures of the model for the time frame 1960-2000 are compared to those obtained from the National Centers for Environmental Prediction observations. A spatial correlation analysis and mean value comparison are performed, showing good agreement. A brief general discussion about the statistics of trend detection is presented. The domain of interest is the Northern Hemisphere (NH) because of the higher reliability of both the model results and the observations. The accuracy that this AOM has in describing the observed regional and NH climate trends makes it reliable in forecasting future climate changes.

Lucarini, Valerio↗
NASA NTRS2003

Observed and Modeled Trends in Southern Ocean Sea Ice

Conceptual models and global climate model (GCM) simulations have both indicated the likelihood of an enhanced sensitivity to climate change in the polar regions, derived from the positive feedbacks brought about by the polar abundance of snow and ice surfaces. Some models further indicate that the changes in the polar regions can have a significant impact globally. For instance, 37% of the temperature sensitivity to a doubling of atmospheric CO2 in simulations with the GCM of the Goddard Institute for Space Studies (GISS) is attributable exclusively to inclusion of sea ice variations in the model calculations. Both sea ice thickness and sea ice extent decrease markedly in the doubled CO, case, thereby allowing the ice feedbacks to occur. Stand-alone sea ice models have shown Southern Ocean hemispherically averaged winter ice-edge retreats of 1.4 deg latitude for each 1 K increase in atmospheric temperatures. Observations, however, show a much more varied Southern Ocean ice cover, both spatially and temporally, than many of the modeled expectations. In fact, the satellite passive-microwave record of Southern Ocean sea ice since late 1978 has revealed overall increases rather than decreases in ice extents, with ice extent trends on the order of 11,000 sq km/year. When broken down spatially, the positive trends are strongest in the Ross Sea, while the trends are negative in the Bellingshausen/Amundsen Seas. Greater spatial detail can be obtained by examining trends in the length of the sea ice season, and those trends show a coherent picture of shortening sea ice seasons throughout almost the entire Bellingshausen and Amundsen Seas to the west of the Antarctic Peninsula and in the far western Weddell Sea immediately to the east of the Peninsula, with lengthening sea ice seasons around much of the rest of the continent. This pattern corresponds well with the spatial pattern of temperature trends, as the Peninsula region is the one region in the Antarctic with a strong record of temperature increases. Still, although the patterns of the temperature and ice changes match fairly well, there is a substantial ways to go before these patterns are understood (and can be modeled) in the full context of global change.

Parkinson, Claire L.↗
NASA NTRS2012

Earth System Modeling and Field Experiments in the Arctic-Boreal Zone - Report from a NASA Workshop

Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources.

Sellers, Piers↗
NASA NTRS2000

Slow and Steady: Ocean Circulation. The Influence of Sea Surface Height on Ocean Currents

The study of ocean circulation is vital to understanding how our climate works. The movement of the ocean is closely linked to the progression of atmospheric motion. Winds close to sea level add momentum to ocean surface currents. At the same time, heat that is stored and transported by the ocean warms the atmosphere above and alters air pressure distribution. Therefore, any attempt to model climate variation accurately must include reliable calculations of ocean circulation. Unlike movement of the atmosphere, movement of the ocean's waters takes place mostly near the surface. The major patterns of surface circulation form gigantic circular cells known as gyres. They are categorized according to their general location-equatorial, subtropical, subpolar, and polar-and may run across an entire ocean. The smaller-scale cell of ocean circulation is known' as an eddy. Eddies are much more common than gyres and much more difficult to track in computer simulations of ocean currents.

Haekkinen, Sirpa↗
NASA NTRS2018

The Ocean Carbon States Database: A Proof-of-Concept Application of Cluster Analysis in the Ocean Carbon Cycle

In this paper, we present a database of the basic regimes of the carbon cycle in the ocean, the 'ocean carbon states', as obtained using a data mining/pattern recognition technique in observation-based as well as model data. The goal of this study is to establish a new data analysis methodology, test it and assess its utility in providing more insights into the regional and temporal variability of the marine carbon cycle. This is important as advanced data mining techniques are becoming widely used in climate and Earth sciences and in particular in studies of the global carbon cycle, where the interaction of physical and biogeochemical drivers confounds our ability to accurately describe, understand, and predict CO2 concentrations and their changes in the major planetary carbon reservoirs. In this proof-of-concept study, we focus on using well-understood data that are based on observations, as well as model results from the NASA Goddard Institute for Space Studies (GISS) climate model. Our analysis shows that ocean carbon states are associated with the subtropical-subpolar gyre during the colder months of the year and the tropics during the warmer season in the North Atlantic basin. Conversely, in the Southern Ocean, the ocean carbon states can be associated with the subtropical and Antarctic convergence zones in the warmer season and the coastal Antarctic divergence zone in the colder season. With respect to model evaluation, we find that the GISS model reproduces the cold and warm season regimes more skillfully in the North Atlantic than in the Southern Ocean and matches the observed seasonality better than the spatial distribution of the regimes. Finally, the ocean carbon states provide useful information in the model error attribution. Model air-sea CO2 flux biases in the North Atlantic stem from wind speed and salinity biases in the subpolar region and nutrient and wind speed biases in the subtropics and tropics. Nutrient biases are shown to be most important in the Southern Ocean flux bias.

carbon cycle↗
DOE OSTI2024

Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt

Abstract. Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predicted significant mass loss only with near-complete removal of the ice shelf, the ocean warming necessary for this was deemed unlikely. Recent climate projections through 2300 indicate that sufficient ocean warming is a distinct possibility after 2100. This work explores the impact of parametric uncertainty on projections of the response of the Lambert–Amery system (hereafter “the Amery sector”) to abrupt ocean warming through Bayesian calibration of a perturbed-parameter ice-sheet model ensemble. We address the computational cost of uncertainty quantification for ice-sheet model projections via statistical emulation, which employs surrogate models for fast and inexpensive parameter space exploration while retaining critical features of the high-fidelity simulations. To this end, we build Gaussian process (GP) emulators from simulations of the Amery sector at a medium resolution (4–20 km mesh) using the Model for Prediction Across Scales (MPAS)-Albany Land Ice (MALI) model. We consider six input parameters that control basal friction, ice stiffness, calving, and ice-shelf basal melting. From these, we generate 200 perturbed input parameter initializations using space filling Sobol sampling. For our end-to-end probabilistic modeling workflow, we first train emulators on the simulation ensemble and then calibrate the input parameters using observations of the mass balance, grounding line movement, and calving front movement with priors assigned via expert knowledge. Next, we use MALI to project a subset of simulations to 2300 using ocean and atmosphere forcings from a climate model for both low- and high-greenhouse-gas-emission scenarios. From these simulation outputs, we build multivariate emulators by combining GP regression with principal component dimension reduction to emulate multivariate sea-level contribution time series data from the MALI simulations. We then use these emulators to propagate uncertainty from model input parameters to predictions of glacier mass loss through 2300, demonstrating that the calibrated posterior distributions have both greater mass loss and reduced variance compared to the uncalibrated prior distributions. Parametric uncertainty is large enough through about 2130 that the two projections under different emission scenarios are indistinguishable from one another. However, after rapid ocean warming in the first half of the 22nd century, the projections become statistically distinct within decades. Overall, this study demonstrates an efficient Bayesian calibration and uncertainty propagation workflow for ice-sheet model projections and identifies the potential for large sea-level rise contributions from the Amery sector of the Antarctic Ice Sheet after 2100 under high-greenhouse-gas-emission scenarios.

54 ENVIRONMENTAL SCIENCES↗